Data Governance

The Key to Integration, Balance, & Transformation

Table of Contents

  1. Summary
  2. Facets of Governance
  3. Culture Shock?
  4. Governance as Integration Layer
  5. Order + Facilitation = Data-Driven Coordination
  6. About Andrew Brust

1. Summary

The current era of analytics is one of extreme contrasts. More than ever, organizations are being encouraged to, or already have bought into the idea that they must leverage the full value of their data for strategic and competitive advantage. They must build data literacy, encourage a data-driven mindset, and instill in their team the discipline of analyzing data to the point that doing so is almost second nature. But organizations are conditioned also to be vigilant in protecting their data, to comply with new privacy regulations such as GDPR and CCPA, and some have learned the hard lessons of high-profile data breaches.

This combination of maintaining a proactive data-driven mindset and a defensive data protection regime can, at times, seem almost schizophrenic. So how can these seemingly conflicting goals be harmonized and brought into equilibrium? Data governance is the key to establishing a blended, balanced approach to address the needs of data culture with the requirements of data protection. By combining curation of data to make it discoverable, and control over that data to keep it safe, organizations can, with hard work and careful planning, rationalize these needs and make it all work. Enlightened organizations can enable data democratization with governance across on-premises data lakes, cloud-based databases and analytics platforms to make the data within those repositories available and drive new business insights.

To be sure, this combination of curation, control, and data democratization is easier said than done. But getting there is well within reach, attainable by most any organization that is serious about attaining it. And those organizations that do will find themselves in a virtuous cycle of continuous growth in data availability, accompanied by a maximizing of that data’s value. The ethos of data governance and data-driven thinking yields a perpetual data dividend.

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